Formation of Secondary Organic Aerosol from the Heterogeneous Oxidation by Ozone of a Phytoplankton Culture
Bibliographic record
Abstract
The sea surface microlayer (SSML) is often present at the ocean interface and provides a unique environment for chemical reactions to occur. One such reaction is the heterogeneous oxidation of the SSML components with ozone, which is hypothesized to be an important source of volatile compounds that may participate in marine aerosol formation and growth. To better understand this source, a biologically relevant model SSML is constructed using axenic Thalassiosira pseudonana cultures. This model SSML is shown to be reasonably reproducible for repeated experiments with a biological system and offers considerably more chemical and morphological complexities than single-molecule SSML representations for trying to understand the impact of marine biological processes on the atmosphere. Using proton transfer reaction mass spectrometry, this study demonstrates that C7–C10 gas-phase carbonyls arise from the oxidation of the model SSML with ozone. The ability of gas-phase products of ozone oxidation at the SSML to form aerosol particles was investigated with a scanning mobility particle sizer analyzer to determine the particle size and concentration of newly formed ultrafine aerosol particles. These particles are confirmed to be secondary organic aerosol (SOA) by analyzing their composition with an aerosol mass spectrometer, indicating that the source of the aerosol precursors is the organic material generated by the T. pseudonana cultures. The rates of SOA and carbonyl production are larger for 21 day-old cultures than for 7 day-old cultures, likely due to the release of the organic material from cell lysis in the older cultures. By demonstrating that the heterogeneous oxidation of the SSML forms SOA precursors that contribute to aerosol growth, this study emphasizes the importance of biological processes on the chemical reactions that can occur within the SSML.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".